Pathogenesis of Pneumococcal Pneumonia in Cyclophosphamide-Induced Leukopenia in Mice
Bibliographic record
Abstract
Streptococcus pneumoniae pneumonia frequently occurs in leukopenic hosts, and most patients subsequently develop lung injury and septicemia. However, few correlations have been made so far between microbial growth, inflammation, and histopathology of pneumonia in specific leukopenic states. In the present study, the pathogenesis of pneumococcal pneumonia was investigated in mice rendered leukopenic by the immunosuppressor antineoplastic drug cyclophosphamide. Compared to the immunocompetent state, cyclophosphamide-induced leukopenia did not hamper interleukin-1 (IL-1), IL-6, macrophage inflammatory protein-1 (MIP-1), MIP-2, and monocyte chemotactic protein-1 secretion in infected lungs. Leukopenia did not facilitate bacterial dissemination into the bloodstream despite enhanced bacterial proliferation into lung tissues. Pulmonary capillary permeability and edema as well as lung injury were enhanced in leukopenic mice despite the absence of neutrophilic and monocytic infiltration into their lungs, suggesting an important role for bacterial virulence factors and making obvious the fact that neutrophils are ultimately not required for lung injury in this model. Scanning and transmission electron microscopy revealed extensive disruption of alveolar epithelium and a defect in surfactant production, which were associated with alveolar collapse, hemorrhage, and fibrin deposits in alveoli. These results contrast with those observed in immunocompetent animals and indicate that leukopenic hosts suffering from pneumococcal pneumonia are at a higher risk of developing diffuse alveolar damage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".